Results 111 to 120 of about 5,165 (285)
Novel High-Efficiency Nanocomposite Gate Design of Quantum-Dot Cellular Automata Based on Deep Learning. [PDF]
Comput Intell Neurosci, 2022 Zhu Y, Ren S, Li X.
europepmc +1 more source
Probabilistic modeling of quantum-dot cellular automata
, 2023 As CMOS scaling faces a technological barrier in the near future, novel design paradigms are being proposed to keep up with the ever growing need for computation power and speed. Most of these novel technologies have device sizes comparable to atomic and molecular scales.
openaire +2 more sources
Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.The systematic design of memristor‐based neural network is provided by analog conductance state parameters to accurately emulate the software‐based high‐resolution weight at discrete device level. The requirement of discrete analog conductance of memristor device is measured as ≈50 states with nonlinearity value of ≈0.142 within the deviation range of ...
Jingon Jang, Yoonseok Song, Sungjun Park
wiley +1 more source
Non-Restoring Array Divider Using Optimized CAS Cells Based on Quantum-Dot Cellular Automata with Minimized Latency and Power Dissipation for Quantum Computing. [PDF]
Nanomaterials (Basel), 2022 Kim HI, Jeon JC.
europepmc +1 more source
Implementing a Quantum CNOT and Quantum Memory Using a Quantum-Dot Cellular Automata Array
, 2013 In this work, we develop a method to use Quantum- Dot Cellular Automata (QCA) for universal quantum computing. This method is based conceptually on refocusing in NMR systems.
Sheikholeslam, Seyed Arash +1 more
core
Device‐Level Implementation of Reservoir Computing With Memristors
Advanced Intelligent Systems, EarlyView.Reservoir computing (RC) is an emerging computing scheme that employs a reservoir and a single readout layer, which can be actualized in the nanoscale with memristors. As a comprehensive overview, the principles of RC and the switching mechanisms of memristors are discussed, followed by actual demonstrations of memristor‐based RC and the remaining ...
Sunbeom Park, Hyojung Kim, Ho Won Jang
wiley +1 more source
Advanced Intelligent Systems, EarlyView.Droplet‐based microfluidics enables precise, high‐throughput microscale reactions but continues to face challenges in scalability, reproducibility, and data complexity. This review examines how artificial intelligence enhances droplet generation, detection, sorting, and adaptive control and discusses emerging opportunities for clinical and industrial ...
Junyan Lai +10 more
wiley +1 more source
Advanced Intelligent Systems, EarlyView.This study provides an introduction to Bayesian optimisation targeted for experimentalists. It explains core concepts, surrogate modelling, and acquisition strategies, and addresses common real‐world challenges such as noise, constraints, mixed variables, scalability, and automation.
Chuan He +2 more
wiley +1 more source
Advanced Intelligent Systems, EarlyView.This review explores the transformative impact of artificial intelligence on multiscale modeling in materials research. It highlights advancements such as machine learning force fields and graph neural networks, which enhance predictive capabilities while reducing computational costs in various applications.
Artem Maevskiy +2 more
wiley +1 more source
Recent Trends in Metabolomics by NMR Spectroscopy
Angewandte Chemie, EarlyView.AI tools were applied to analyze more than 5 000 publications indexed in Scopus (2018–2025), identifying key trends and research directions in NMR‐based metabolomics. The artificial intelligence‐assisted workflow classified papers into six main fields of application, human health, food and nutrition, veterinary science, plants, environment, and ...
Giorgio Di Paco +6 more
wiley +2 more sources