Results 161 to 170 of about 21,815 (240)

Noise-robust optimization of quantum machine learning models for polymer properties using a simulator and validated on the IonQ quantum computer. [PDF]

Sci Rep, 2022
Ishiyama Y, Nagai R, Mieda S, Takei Y, Minato Y, Natsume Y.   +5 more
europepmc   +1 more source

Reconfigurable, Non‐Volatile Switching in WO3 Film for Resistive Memory and Multistate Programming Toward Energy‐Efficient Neuromorphic Computing Applications

Advanced Electronic Materials, EarlyView.
WO3${\rm WO}_3$ based resistive switching device was precisely controlled and shows the reconfigurable, non‐volatile switching which can be programmable to multi‐resistance states for memory applications. The memory device can also be utilised for low energy neuromorphic application.
Keval Hadiyal, Nagarajan Raghavan, Ramesh Mohan Thamankar   +2 more
wiley   +1 more source

An integrated strategy based on radiomics and quantum machine learning: diagnosis and clinical interpretation of pulmonary ground-glass nodules. [PDF]

BMC Med Imaging
Huang X, Xu F, Zhu W, Yao L, He J, Su J, Zhao W, Hu H.   +7 more
europepmc   +1 more source

Quantum Machine Learning Algorithms for Drug Discovery Applications. [PDF]

J Chem Inf Model, 2021
Batra K, Zorn KM, Foil DH, Minerali E, Gawriljuk VO, Lane TR, Ekins S.   +6 more
europepmc   +1 more source

Recent Advances in Programmable Metasurfaces and Meta‐Devices

Advanced Electronic Materials, EarlyView.
Programmable metasurfaces enable various novel functionalities by dynamically tuning electromagnetic wavefronts. This article provides a comprehensive review of recent advances in microwave and terahertz programmable metasurfaces, covering electrical, thermal, optical, and mechanical control mechanisms.
Linda Shao, Chong He, Nan Wang, Liming Si, Weiren Zhu   +4 more
wiley   +1 more source

Comparative Insights and Overlooked Factors of Interphase Chemistry in Alkali Metal‐Ion Batteries

Advanced Energy Materials, EarlyView.
This review presents a comparative analysis of Li‐, Na‐, and K‐ion batteries, focusing on the critical role of electrode–electrolyte interphases. It especially highlights overlooked aspects such as SEI/CEI misconceptions, binder effects, and self‐discharge relevance, emphasizing the limitations of current understanding and offering strategies for ...
Changhee Lee, Zachary T. Gossage, Shinichi Kumakura, Shinichi Komaba   +3 more
wiley   +1 more source

Quantum machine learning with Adaptive Boson Sampling via post-selection. [PDF]

Nat Commun
Hoch F, Caruccio E, Rodari G, Francalanci T, Suprano A, Giordani T, Carvacho G, Spagnolo N, Koudia S, Proietti M, Liorni C, Cerocchi F, Albiero R, Di Giano N, Gardina M, Ceccarelli F, Corrielli G, Chabaud U, Osellame R, Dispenza M, Sciarrino F.   +20 more
europepmc   +1 more source

Smart Exploration of Perovskite Photovoltaics: From AI Driven Discovery to Autonomous Laboratories

Advanced Energy Materials, EarlyView.
In this review, we summarize the fundamentals of AI in automated materials science, and review AI applications in perovskite solar cells. Then, we sum up recent progress in AI‐guided manufacturing optimization, and highlight AI‐driven high‐throughput and autonomous laboratories.
Wenning Chen, Zheyu Zhang, Kelvian T. Mularso, Bonghyun Jo, Hyun Suk Jung   +4 more
wiley   +1 more source

Quantum machine learning-based electrokinetic mining for the identification of nanoparticles and exosomes with minimal training data. [PDF]

Bioact Mater
Thakur A, Santos Bezerra PC, Abhishek, Zeng S, Zhang K, Treptow W, Luna A, Dougherty U, Kwesi A, Huang IR, Bestvina C, Garassino MC, Duan F, Gokhale Y, Duan B, Chen Y, Lian Q, Bissonnette M, Huang J, Chen HJ.   +19 more
europepmc   +1 more source

Quantum Machine Learning Architecture for COVID-19 Classification Based on Synthetic Data Generation Using Conditional Adversarial Neural Network. [PDF]

Cognit Comput, 2022
Amin J, Sharif M, Gul N, Kadry S, Chakraborty C.   +4 more
europepmc   +1 more source