The 3D Printing of Nanocomposites for Wearable Biosensors: Recent Advances, Challenges, and Prospects

Recent advances in nanomaterials for wearable devices: classification, synthesis, and applications

Wearable devices have a wide range of applications in mobile electronics, energy storage, human movement and health monitoring due to their flexibility, comfort and portability. Nanomaterials have excellent electrical conductivity and mechanical properties due to being in the nanoscale range with small size and surface effects that alter electrical properties. This paper focuses on the progress of research on advanced nanomaterials in the wearable field, including the classification of nanomaterials, physical, chemical, microwave-assisted, and biological synthesis for nanomaterials, as well as spinning, textile coating, and three-dimensional printing of fabricating functional layers of nanodevices. In addition, its importance in thermal management devices, telemedicine and monitoring, assistance for the disabled and mental health and sleep monitoring is analyzed. Finally, the current challenges and future directions of the field are discussed. This review will be of great interest and inspiration for developing and improving novel nanomaterials and advanced wearable nanodevices.

Electrochemically Active Materials for Tissue-Interfaced Soft Biochemical Sensing

Tissue-interfaced soft biochemical sensing represents a crucial approach to personalized healthcare by employing electrochemically active materials to monitor biochemical signals at the tissue interface in real time, either noninvasively or through implantation. These soft biochemical sensors can be integrated with various biological tissues, such as neural, gastrointestinal, ocular, cardiac, skin, muscle, and bone, adapting to their unique mechanical and biochemical environments. Sensors employing materials like conductive polymers, composites, metals, metal oxides, and carbon-based nanomaterials have demonstrated capabilities in applications, such as continuous glucose monitoring, neural activity mapping, and real-time metabolite detection, enhancing diagnostics and treatment monitoring across a range of medical fields. Next-generation tissue-interfaced biosensors that enable multimodal and multiplexed measurement of biochemical markers and physiological parameters could be transformative for personalized medicine, allowing for high-resolution, time-resolved historical monitoring of an individual's health status. In this review, we summarize current trends in the field to provide insights into the challenges and future trajectory of tissue-interfaced soft biochemical sensors, highlighting their potential to revolutionize personalized medicine and improve patient outcomes.

Smart Health Monitoring: Review of Electrochemical Biosensors for Cortisol Monitoring

Cortisol, also known as the stress hormone, is a crucial corticosteroid hormone that significantly increases secretion in the human body when facing notable stress. Monitoring cortisol levels is crucial for personal stress management and the diagnosis and treatment of certain diseases. Electrochemical biosensors combine the efficient sensitivity of electrochemical technology with the high specificity of biological recognition processes, making them widely applicable in the analysis of human body fluid components. This work outlines the working mechanism of cortisol electrochemical biosensors, focusing particularly on sensing elements such as antibodies, aptamers, and molecularly imprinted polymers. It provides detailed explanations of the operational principles of these different recognition elements. This work summarizes and evaluates the latest advancements in electrochemical biosensors for detecting cortisol in human body fluids, discussing the influence of different recognition elements on sensor design and electrochemical performance. Subsequently, through a comparative analysis of various sensor performances, the work further discusses the challenges in translating laboratory achievements into practical applications, including enhancing key metrics such as sensor reusability, reproducibility, long-term stability, continuous monitoring capability, and response time. Finally, it offers insights and recommendations for achieving real-time, continuous, and long-term monitoring with cortisol electrochemical biosensors.

Toward Intelligent Materials with the Promise of Self-Healing Hydrogels in Flexible Devices

Flexible sensors are revolutionizing wearable and implantable devices, with conductive hydrogels emerging as key materials due to their biomimetic structure, biocompatibility, tunable transparency, and stimuli-responsive electrical properties. However, their fragility and limited durability pose significant challenges for broader applications. Drawing inspiration from the self-healing capabilities of natural organisms like mussels, researchers are embedding self-repair mechanisms into hydrogels to improve their reliability and lifespan. This review highlights recent advances in self-healing (SH) conductive hydrogels, focusing on synthesis methods, healing mechanisms, and strategies to enhance multifunctionality. It also explores their wide-ranging applications, including in vivo signal monitoring, wearable biochemical sensors, supercapacitors, flexible displays, triboelectric nanogenerators, and implantable bioelectronics. While progress has been made, challenges remain in balancing self-healing efficiency, mechanical strength, and sensing performance. This review offers insights into overcoming these obstacles and discusses future research directions for advancing SH hydrogel-based bioelectronics, aiming to pave the way for durable, high-performance devices in next-generation wearable and implantable technologies.

Nanomaterials for Energy Storage Systems-A Review

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.

3D Printing in Biocatalysis and Biosensing: From General Concepts to Practical Applications

3D printing has matured into a versatile technique that offers researchers many different printing methods and materials with varying properties. Nowadays, 3D printing is deployed within a myriad of different applications, ranging from chemistry to biotechnology -including bioanalytics, biocatalysis or biosensing. Due to its inherent design flexibility (which enables rapid prototyping) and ease of use, 3D printing facilitates the relatively quick and easy creation of new devices with unprecedented functions.. This review article describes how 3D printing can be employed for research in the fields of biochemistry and biotechnology, and specifically for biocatalysis and biosensor applications. We survey different relevant 3D printing techniques, as well as the surface activation and functionalization of 3D-printed materials. Finally, we show how 3D printing is used for the fabrication of reaction ware and enzymatic assays in biocatalysis research, as well as for the generation of biosensors using aptamers, antibodies, and enzymes as recognition elements.

A physiological perspective of the relevance of sweat biomarkers and their detection by wearable microfluidic technology: A review

The great majority of published microfluidic wearable platforms for sweat sensing focus on the development of the technology to fabricate the device, the integration of sensing materials and actuators and the fluidics of sweat within the device. However, very few papers have discussed the physiological relevance of the metabolites measured using these novel approaches. In fact, some of the analytes present in sweat, which serve as biomarkers in blood, do not show a correlation with blood levels. This discrepancy can be attributed to factors such as contamination during measurements, the metabolism of sweat glands, or challenges in obtaining significant samples. The objective of this review is to present a critical and meaningful insight into the real applicability and potential use of wearable technology for improving health and sport performance. It also discusses the current limitations and future challenges of microfluidics, aiming to provide accurate information about the actual needs in this field. This work is expected to contribute to the future development of more suitable wearable microfluidic technology for health and sports science monitoring, using sweat as the biofluid for analysis.

Investigating Laser Ablation Process Parameters for the Fabrication of Customized Microneedle Arrays for Therapeutic Applications

Microneedles are an innovation in the field of medicine that have the potential to revolutionize drug delivery, diagnostics, and cosmetic treatments. This innovation provides a minimally invasive means to deliver drugs, vaccines, and other therapeutic substances into the skin. This research investigates the design and manufacture of customized microneedle arrays using laser ablation. Laser ablation was performed using an ytterbium laser on a polymethyl methacrylate (PMMA) substrate to create a mold for casting polydimethylsiloxane (PDMS) microneedles. An experimental design was conducted to evaluate the effect of process parameters including laser pulse power, pulse width, pulse repetition, interval between pulses, and laser profile on the desired geometry of the microneedles. The analysis of variance (ANOVA) model showed that lasing interval, laser power, and pulse width had the highest influence on the output metrics (diameter and height) of the microneedle. The microneedle dimensions showed an increase with higher pulse width and vice versa with an increase in pulse interval. A response surface model indicated that the laser pulse width and interval (independent variables) significantly affect the response diameter and height (dependent variable). A predictive model was generated to predict the microneedle topology and aspect ratio varying from 0.8 to 1.5 based on the variation in critical input process parameters. This research lays the foundation for the design and fabrication of customized microneedles based on variations in specific input parameters for therapeutic applications in dermal sensors, drug delivery, and vaccine delivery.

Nanoimprint Lithography for Next-Generation Carbon Nanotube-Based Devices

This research reports the development of 3D carbon nanostructures that can provide unique capabilities for manufacturing carbon nanotube (CNT) electronic components, electrochemical probes, biosensors, and tissue scaffolds. The shaped CNT arrays were grown on patterned catalytic substrate by chemical vapor deposition (CVD) method. The new fabrication process for catalyst patterning based on combination of nanoimprint lithography (NIL), magnetron sputtering, and reactive etching techniques was studied. The optimal process parameters for each technique were evaluated. The catalyst was made by deposition of Fe and Co nanoparticles over an alumina support layer on a Si/SiO2 substrate. The metal particles were deposited using direct current (DC) magnetron sputtering technique, with a particle ranging from 6 nm to 12 nm and density from 70 to 1000 particles/micron. The Alumina layer was deposited by radio frequency (RF) and reactive pulsed DC sputtering, and the effect of sputtering parameters on surface roughness was studied. The pattern was developed by thermal NIL using Si master-molds with PMMA and NRX1025 polymers as thermal resists. Catalyst patterns of lines, dots, and holes ranging from 70 nm to 500 nm were produced and characterized by scanning electron microscopy (SEM) and atomic force microscopy (AFM). Vertically aligned CNTs were successfully grown on patterned catalyst and their quality was evaluated by SEM and micro-Raman. The results confirm that the new fabrication process has the ability to control the size and shape of CNT arrays with superior quality.

Bridging Nanomanufacturing and Artificial Intelligence-A Comprehensive Review

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.

3D Printed Nanosensors for Cancer Diagnosis: Advances and Future Perspective

Cancer is the leading cause of mortality worldwide, requiring continuous advancements in diagnosis and treatment. Traditional methods often lack sensitivity and specificity, leading to the need for new methods. 3D printing has emerged as a transformative tool in cancer diagnosis, offering the potential for precise and customizable nanosensors. These advancements are critical in cancer research, aiming to improve early detection and monitoring of tumors. In current times, the usage of the 3D printing technique has been more prevalent as a flexible medium for the production of accurate and adaptable nanosensors characterized by exceptional sensitivity and specificity. The study aims to enhance early cancer diagnosis and prognosis by developing advanced 3D-printed nanosensors using 3D printing technology. The research explores various 3D printing techniques, design strategies, and functionalization strategies for cancer-specific biomarkers. The integration of these nanosensors with detection modalities like fluorescence, electrochemical, and surface-enhanced Raman spectroscopy is also evaluated. The study explores the use of inkjet printing, stereolithography, and fused deposition modeling to create nanostructures with enhanced performance. It also discusses the design and functionalization methods for targeting cancer indicators. The integration of 3D-printed nanosensors with multiple detection modalities, including fluorescence, electrochemical, and surface-enhanced Raman spectroscopy, enables rapid and reliable cancer diagnosis. The results show improved sensitivity and specificity for cancer biomarkers, enabling early detection of tumor indicators and circulating cells. The study highlights the potential of 3D-printed nanosensors to transform cancer diagnosis by enabling highly sensitive and specific detection of tumor biomarkers. It signifies a pivotal step forward in cancer diagnostics, showcasing the capacity of 3D printing technology to produce advanced nanosensors that can significantly improve early cancer detection and patient outcomes.