Hydrogen‐Bond–Driven Ion Retention in Electrolyte‐Gated Synaptic Transistors
Anion molecular design governs ion–polymer interactions in electrolyte‐gated synaptic transistors. Asymmetric anions induce hydrogen‐bond interactions that suppress ion back‐diffusion and stabilize doping, enabling enhanced nonvolatile synaptic properties.
Donghwa Lee +5 more
wiley +1 more source
Scalable parameterized quantum circuits classifier
As a generalized quantum machine learning model, parameterized quantum circuits (PQC) have been found to perform poorly in terms of classification accuracy and model scalability for multi-category classification tasks. To address this issue, we propose a
Xiaodong Ding +5 more
doaj +1 more source
Quantum Machine Learning for Malware Classification
In a context of malicious software detection, machine learning (ML) is widely used to generalize to new malware. However, it has been demonstrated that ML models can be fooled or may have generalization problems on malware that has never been seen. We investigate the possible benefits of quantum algorithms for classification tasks.
Grégoire Barrué, Tony Quertier
openaire +2 more sources
Robust Classification with Adiabatic Quantum Optimization [PDF]
17 pages, 5 figures, accepted by ICML ...
Vasil S. Denchev +3 more
openaire +2 more sources
Orbital Geometry‐Governed Response of Pressure‐Tunable Quantum Defects in hBN
Defects in hBN act as ultrasensitive quantum manometers when the energy of the intradefect optical transitions is modified by lattice compression. The orbital geometry of the electron wave functions governs how electron hopping and Coulomb interactions react uniquely to the reduction of the van der Waals gap and in‐plane compression, leading to robust ...
Magdalena Grzeszczyk +6 more
wiley +1 more source
Quantum neural networks facilitating quantum state classification
The classification of quantum states into distinct classes poses a significant challenge. In this study, we address this problem using quantum neural networks in combination with a problem-inspired circuit and customised as well as predefined ansätz. To facilitate the resource-efficient quantum state classification, we construct the dataset of quantum ...
Diksha Sharma +3 more
openaire +2 more sources
Nanotherapies for Atherosclerosis: Targeting, Catalysis, and Energy Transduction
Atherosclerosis management is hindered by poor drug targeting and plaque heterogeneity. Nanotechnology overcomes these barriers via three core strategies: (1) target‐engineered nanocarriers that achieve lesion‐specific precision via ligand modification, biomimetic camouflage, stimuli‐responsive release, and self‐propelling nanomotors; (2) catalytic ...
Yuqi Yang +4 more
wiley +1 more source
Quantum-Classical Framework for Tamil Handwritten Character Classification using SQCNN and Bayesian-Optimized VQC [PDF]
Handwritten character recognition for Tamil characters is challenging because of the characters displaying high level of similarity between them and also due to the variations in different handwriting styles.
M R Kavinmathi, Murugappan Abirami
doaj +1 more source
Epidermal Patch Technologies for Integrated Healthcare and Infection Management
Epidermal patches have evolved from simple wound coverings into multifunctional, skin‐conformable platforms integrating drug delivery, biosensing, and therapeutic functionalities. This review highlights their material innovations, fabrication strategies, and intelligent designs, including hydrogels, microneedles, and flexible electronics, while ...
Yuqi Wang +7 more
wiley +1 more source
Quantum Cellular Automata for Quantum Error Correction and Density Classification
Quantum cellular automata are alternative quantum-computing paradigms to quantum Turing machines and quantum circuits. Their working mechanisms are inherently automated, therefore measurement free, and they act in a translation invariant manner on all cells/qudits of a register, generating a global rule that updates cell states locally, i.e., based ...
Guedes, T. L. M. +2 more
openaire +6 more sources

