The capabilities of nanoelectronic 2-D materials for bio-inspired computing and drug delivery indicate their significance in modern drug design

神经形态工程学 计算机科学 纳米技术 高效能源利用 计算 冯·诺依曼建筑 计算机体系结构 计算机工程 材料科学 分布式计算 人工智能 人工神经网络 工程类 算法 电气工程 操作系统
作者
Parichehr Hassanzadeh
出处
期刊:Life Sciences [Elsevier BV]
卷期号:279: 119272-119272 被引量:16
标识
DOI:10.1016/j.lfs.2021.119272
摘要

Remarkable advancements in the computational techniques and nanoelectronics have attracted considerable interests for development of highly-sophisticated materials (Ms) including the theranostics with optimal characteristics and innovative delivery systems. Analyzing the huge amounts of multivariate data and solving the newly-emerged complicated problems including the healthcare-related ones have created increasing demands for improving the computational speed and minimizing the consumption of energy. Shifting towards the non-von Neumann approaches enables performing specific computational tasks and optimizing the processing of signals. Besides usefulness for neuromorphic computing and increasing the efficiency of computation energy, 2-D electronic Ms are capable of optical sensing with ultra-fast and ultra-sensitive responses, mimicking the neurons, detection of pathogens or biomolecules, and prediction of the progression of diseases, assessment of the pharmacokinetics/pharmacodynamics of therapeutic candidates, mimicking the dynamics of the release of neurotransmitters or fluxes of ions that might provide a deeper knowledge about the computations and information flow in the brain, and development of more effective treatment protocols with improved outcomes. 2-D Ms appear as the major components of the next-generation electronically-enabled devices for highly-advanced computations, bio-imaging, diagnostics, tissue engineering, and designing smart systems for site-specific delivery of therapeutics that might result in the reduced adverse effects of drugs and improved patient compliance. This manuscript highlights the significance of 2-D Ms in the neuromorphic computing, optimizing the energy efficiency of the multi-step computations, providing novel architectures or multi-functional systems, improved performance of a variety of devices and bio-inspired functionalities, and delivery of theranostics.
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