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Fibrous wearable and implantable devices have emerged as a promising technology, offering a range of new solutions for minimally invasive monitoring of human health. Compared to traditional biomedical devices, fibers offer a possibility for a modular design compatible with large-scale manufacturing and a plethora of advantages including mechanical compliance, breathability, and biocompatibility. The new generation of fibrous biomedical devices can revolutionize easy-to-use and accessible health monitoring systems by serving as building blocks for most common wearables such as fabrics and clothes. Despite significant progress in the fabrication, materials, and application of fibrous biomedical devices, there is still a notable absence of a comprehensive and systematic review on the subject. This review paper provides an overview of recent advancements in the development of fibrous wearable and implantable electronics. We categorized these advancements into three main areas: manufacturing processes, platforms, and applications, outlining their respective merits and limitations. The paper concludes by discussing the outlook and challenges that lie ahead for fiber bioelectronics, providing a holistic view of its current stage of development.
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A Perspective on Democratizing Mechanical Testing: Harnessing Artificial Intelligence to Advance Sustainable Material Adoption and Decentralized Manufacturing
Abstract Democratized mechanical testing offers a promising solution for enabling the widespread adoption of recycled and renewably sourced feedstocks. Locally sourced, sustainable materials often exhibit variable mechanical properties, which limit their large-scale use due to tight manufacturing specifications. Wider access to mechanical testing at the local level can address this challenge by collecting data on the variable properties of sustainable feedstocks, allowing for the development of appropriate, uncertainty-aware mechanics frameworks. These frameworks are essential for designing custom manufacturing approaches that accommodate variable local feedstocks, while ensuring product quality and reliability through post-manufacturing testing. However, traditional mechanical testing apparatuses are too costly and complex for widespread local use by individuals or small, community-based facilities. Despite promising efforts over the past decade to develop more affordable and versatile testing hardware, significant limitations remain in their reliability, adaptability, and ease–of-use. Recent advances in artificial intelligence (AI) present an opportunity to overcome these limitations by reducing human intervention, enhancing instrument reliability, and facilitating data interpretation. AI can thus enable the creation of low-cost, user-friendly mechanical testing infrastructure. Future efforts to democratize mechanical testing are expected to be closely linked with advancements in manufacturing and materials mechanics. This perspective paper highlights the need to embrace AI advancements to facilitate local production from sustainable feedstocks and enhance the development of decentralized, low-/zero-waste supply chains.
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- Award ID(s):
- 2338508
- PAR ID:
- 10596212
- Publisher / Repository:
- The American Society of Mechanical Engineers (ASME)
- Date Published:
- Journal Name:
- Journal of Applied Mechanics
- Volume:
- 91
- Issue:
- 11
- ISSN:
- 0021-8936
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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