Improving Fault-Tolerance in Nano-Computing Circuits Through Design Optimization Using the Electric Method
REST Journal on Data Analytics and Artificial Intelligence · 2025
Nano-Computing. Nano-computing is an emerging field at the intersection of nanotechnology and computing, aimed at developing ultra-small and highly efficient computing systems. By leveraging nanomaterials and nanoscale devices, nano-computing promises to revolutionize traditional computing paradigms, offering unprecedented computing power and compactness. The use of nanoscale components enables faster information processing and lower energy consumption, paving the way for advancements in areas like artificial intelligence, data storage, and medical applications. As researchers delve into the potential of nanocomputing, it opens up exciting possibilities for the future of computing technology. Nano-computing research holds immense significance as it explores the potential of nanoscale materials and devices to revolutionize computing technology. The development of ultra-small and highly efficient computing systems can lead to groundbreaking advancements in various fields, including medicine, electronics, and data processing. Nano-computing offers the promise of unprecedented computing power and energy efficiency, enabling faster information processing and new computing paradigms. The exploration of nanocomputing's capabilities could lead to transformative breakthroughs in artificial intelligence, quantum computing, and data storage, ultimately shaping the future of computing and its impact on society. Methodology: The ELECTRIC method, short for Elimination and Choice Expressing Reality, is a multi-criteria decision-making technique used to assess various alternatives based on multiple criteria. The method involves two stages. First, it eliminates unrealistic options that do not meet the necessary criteria. Next, it helps decision-makers express their preferences by ranking the remaining alternatives. By assigning weightage to each criterion and considering the expressed preferences, the ELECTRIC method quantitatively evaluates the alternatives and identifies the best choice. This method is particularly useful when dealing with complex decision-making scenarios where multiple criteria need to be considered to make a well-informed and objective choice. Alternative: Processing Speed (GHz), Energy Efficiency, Memory Capacity (gigabytes), Scalability, Error Rate, Parallelism. Evaluation preference: Quantum Dot Nanocomputing, DNA Nanocomputing, Carbon Nanotube Nanocomputing, Molecular Nanocomputing. Results: From the result it is seen that Incident Response is got the first rank where as is the Scalability is having the lowest rank.