Results 81 to 90 of about 137,793 (228)

Epidermal Patch Technologies for Integrated Healthcare and Infection Management

Advanced Healthcare Materials, EarlyView.
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, Atakan Tevlek, Pawel L. Urban, Boaz Mizrahi, Onome Ejeromedoghene, Roshan Deen, Yuanjing Lin, Jagan Mohan Dodda   +7 more
wiley   +1 more source

An optimizing method for performance and resource utilization in quantum machine learning circuits

Scientific Reports, 2022
Quantum computing is a new and advanced topic that refers to calculations based on the principles of quantum mechanics. It makes certain kinds of problems be solved easier compared to classical computers.
Tahereh Salehi, Mariam Zomorodi, Pawel Plawiak, Mina Abbaszade, Vahid Salari   +4 more
doaj   +1 more source

Ferroelectric Quantum Dots for Retinomorphic In‐Sensor Computing

Advanced Materials, EarlyView.
This work has provided a protocol for fabricating retinomorphic phototransistors by integrating ferroelectric ligands with quantum dots. The resulting device combines ferroelectricity, optical responsiveness, and low‐power operation to enable adaptive signal amplification and high recognition accuracy under low‐light conditions, while supporting ...
Tingyu Long, Huanyu Zhou, Jaewan Ko, Hongwei Tan, Jaemin Lim, Yanfei Zhao, Daehan Kang, Eojin Yoon, Gyeong‐Tak Go, Somin Kim, Seung‐Woo Lee, Chan‐Yul Park, Hyojun Choi, Hyeran Kim, Hyung Joong Yun, Sung Hyuk Park, Kwan Sik Park, Jeong Woo Park, Mungeun Kim, Yong Soo Cho, Ho Won Jang, Wenqiang Yang, Min Hyuk Park, Wan Ki Bae, Sebastiaan van Dijken, Joona Bang, Tae‐Woo Lee   +26 more
wiley   +1 more source

Supervised learning with quantum enhanced feature spaces

, 2018
Machine learning and quantum computing are two technologies each with the potential for altering how computation is performed to address previously untenable problems.
Chow, Jerry M., Córcoles, Antonio D., Gambetta, Jay M., Harrow, Aram W., Havlicek, Vojtech, Kandala, Abhinav, Temme, Kristan   +6 more
core   +1 more source

Bioinspired Adaptive Sensors: A Review on Current Developments in Theory and Application

Advanced Materials, EarlyView.
This review comprehensively summarizes the recent progress in the design and fabrication of sensory‐adaptation‐inspired devices and highlights their valuable applications in electronic skin, wearable electronics, and machine vision. The existing challenges and future directions are addressed in aspects such as device performance optimization ...
Guodong Gong, You Zhou, Qingxiu Li, Wenyu Zhao, Sunyingyue Geng, Hangfei Li, Yan‐Bing Leng, Shirui Zhu, Guanglong Ding, Yongbiao Zhai, Ziyu Lv, Ye Zhou, Su‐Ting Han   +12 more
wiley   +1 more source

Quantum Machine Learning Playground

IEEE Computer Graphics and Applications
Accepted to IEEE Computer Graphics and Applications.
Pascal Debus, Sebastian Issel, Kilian Tscharke   +2 more
openaire   +3 more sources

Performance of Quantum Annealing Machine Learning Classification Models on ADMET Datasets

IEEE Access
The Quantum Annealer built by D-Wave, known as Advantage, is currently the largest quantum computer in the world, featuring a topology called “Pegasus.” This groundbreaking system opens new possibilities for solving highly complex problems.
Hadi Salloum, Kamil Sabbagh, Vladislav Savchuk, Ruslan Lukin, Osama Orabi, Marat Isangulov, Manuel Mazzara   +6 more
doaj   +1 more source

Artificial Intelligence‐Assisted Workflow for Transmission Electron Microscopy: From Data Analysis Automation to Materials Knowledge Unveiling

Advanced Materials, EarlyView.
AI‐Assisted Workflow for (Scanning) Transmission Electron Microscopy: From Data Analysis Automation to Materials Knowledge Unveiling. Abstract (Scanning) transmission electron microscopy ((S)TEM) has significantly advanced materials science but faces challenges in correlating precise atomic structure information with the functional properties of ...
Marc Botifoll, Ivan Pinto‐Huguet, Enzo Rotunno, Thomas Galvani, Catalina Coll, Payam Habibzadeh Kavkani, Maria Chiara Spadaro, Yann‐Michel Niquet, Martin Børstad Eriksen, Sara Martí‐Sánchez, Georgios Katsaros, Giordano Scappucci, Peter Krogstrup, Giovanni Isella, Andreu Cabot, Gonzalo Merino, Pablo Ordejón, Stephan Roche, Vincenzo Grillo, Jordi Arbiol   +19 more
wiley   +1 more source

Potential and limitations of random Fourier features for dequantizing quantum machine learning [PDF]

Quantum
Quantum machine learning is arguably one of the most explored applications of near-term quantum devices. Much focus has been put on notions of variational quantum machine learning where {parameterized quantum circuits} (PQCs) are used as learning models.
Ryan Sweke, Erik Recio-Armengol, Sofiene Jerbi, Elies Gil-Fuster, Bryce Fuller, Jens Eisert, Johannes Jakob Meyer   +6 more
doaj   +1 more source

Beyond Presumptions: Toward Mechanistic Clarity in Metal‐Free Carbon Catalysts for Electrochemical H2O2 Production via Data Science

Advanced Materials, EarlyView.
Metal‐free carbon catalysts enable the sustainable synthesis of hydrogen peroxide via two‐electron oxygen reduction; however, active site complexity continues to hinder reliable interpretation. This review critiques correlation‐based approaches and highlights the importance of orthogonal experimental designs, standardized catalyst passports ...
Dayu Zhu, Hsi‐wen Wu, Xiao Wang, Jie Zhang   +3 more
wiley   +1 more source